A climate-change vulnerability and adaptation assessment for Brazil's protected areas

Brazil hosts the largest expanse of tropical ecosystems within protected areas (PAs), which shelter biodiversity and support traditional human populations. We assessed the vulnerability to climate change of 993 terrestrial and coastal-marine Brazilian PAs by combining indicators of climatic-change hazard with indicators of PA resilience (size, native vegetation cover, and probability of climate-driven vegetation transition). This combination of indicators allows the identification of broad climate-change adaptation pathways. Seventeen PAs (20,611 km²) were highly vulnerable and located mainly in the Atlantic Forest (7 PAs), Cerrado (6), and the Amazon (4). Two hundred fifty-eight PAs (756,569 km²), located primarily in Amazonia, had a medium vulnerability. In the Amazon and western Cerrado, the projected severe climatic change and probability of climate-driven vegetation transition drove vulnerability up, despite the generally good conservation status of PAs. Over 80% of PAs of high or moderate vulnerability are managed by indigenous populations. Hence, besides the potential risks to biodiversity, the traditional knowledge and livelihoods of the people inhabiting these PAs may be threatened. In at least 870 PAs, primarily in the Atlantic Forest and Amazon, adaptation could happen with little or no intervention due to low climate-change hazard, high resilience status, or both. At least 20 PAs in the Atlantic Forest, Cerrado, and Amazonia should be targeted for stronger interventions (e.g., improvement of ecological connectivity), given their low resilience status. Despite being a first attempt to link vulnerability and adaptation in Brazilian PAs, we suggest that some of the PAs identified as highly or moderately vulnerable should be prioritized for testing potential adaptation strategies in the near future.     

Sampling strategies in the assessment of long‐term exposures to toxic substances in air

The decision to mitigate exposures from vapor intrusion (VI) is typically based on limited data from 24‐hour air samples. It is well documented that these data do not accurately represent long‐term average exposures linked to adverse health effects. Limited decision guidance is currently available to determine the most appropriate sampling strategy, considering the cost of sampling alternatives along with the economic consequences of exposure‐related health effects. We present a decision model that introduces economic and statistical considerations in evaluating alternative VI sampling methods. The model characterizes the best sampling method by factoring economic and health consequences of exposure, the variability of exposure, the cost of sampling and mitigation, and the likelihood of false‐negatives and false‐positives. Decision‐makers can use results to select the sample size that maximizes net benefit. Conceptual and mathematical models are presented linking biological, statistical, and economic considerations to assess the cost and effectiveness of different sampling strategies. The model relates an average exposure concentration, determined statistically, to abatement costs and to the monetary value of health deterioration. The value of the information provided by different strategies is calculated and used to select the optimum sampling method. Simulations show that longer‐term sampling methods tend to be more accurate and cost‐effective than short‐term samples. The ideal sampling strategy shows significant seasonal variation (it is typically optimal to use longer samples in the winter) and also varies significantly with the stringency of regulatory standards. Longer‐term sample collection provides a more accurate representation of average VI exposure and reduces the likelihood of type I and type II errors. This reduces expected costs of mitigation and exposure (e.g., health consequences, legal and regulatory penalties), which in some cases can be quite significant. The model herein shows how these savings are balanced against the additional costs of longer‐term sampling.     

Effects of calcium hydroxide and calcium chloride addition to bentonite in iron ore pelletization.

Pyrite ash is created as waste from the roasting of pyrite ores during the production of sulphuric acid. These processes generate great amounts of pyrite ash waste that is generally land filled. This creates serious environmental pollution due to the release of acids and toxic substances. Pyrite ash waste can be utilized in the iron production industry as a blast furnace feed to process this waste and prevent environmental pollution. The essential parameters affecting the pelletization process of pyrite ash were studied using bentonite as a binder. Experiments were then carried out using bentonite and a mixture of bentonite with calcium hydroxide and calcium chloride in order to make the bentonite more effective. The metallurgical properties of pyrite ash, bentonite, calcium hydroxide, calcium chloride, a mixture of these and sintered pellets were studied using X-ray analysis. The crushing strength tests were carried out to investigate the strength of pyrite ash waste pellets. The results of these analyses showed that pyrite ash can be agglomerated to pellets and used in the iron production industry as a blast furnace feed. The crushing strength of the pellets containing calcium hydroxide and calcium chloride in addition to bentonite was better than the strength of pellets prepared using only bentonite binder.     

Working backwards to move forwards: Graph-based connectivity metrics for reserve network selection

In this paper we apply graph theory in a reserve selection exercise to explore the tradeoffs between maintaining connectivity and minimizing the total area of a protected area network. Rather than focus on a single organism, we used a multi-species approach and looked at the tradeoff curves for organisms with varying dispersal abilities. We first generated the tradeoff curves using a graph-based metric to determine the importance of individual patches for maintaining connectivity. We then performed an analogous set of analyses using patch size as a surrogate measure of importance.     

Assessing the influence of altitude and temperature on biological monitoring of freshwater quality: A preliminary investigation

The effect of altitude and water temperature on biomonitoring of freshwater quality was examined along an unpolluted area (36 km in length) of the upper Río Tajo (central Spain). The macrobenthic and fish communities were studied, and the Biological Monitoring Water Quality (BMWQ) method was applied. As expected, values of altitude and temperature respectively decreased and increased with increasing distance from the river source; these two physical parameters exhibited a negative and significant (P<0.05) correlation coefficient between them. However, despite evident changes in the functional structure of both aquatic communities along the study area, BMWQ scores were similar at all sampling sites. Pearson correlation coefficients between physical and biological parameters were not significant (P>0.05). The BMWQ index only exhibited significant (positive) correlation coefficients with macrobenthic and fish biomasses, indicating that freshwater quality could affect the biological production of fluvial ecosystems. It is concluded that biomonitoring of freshwater quality may be independent of the influence of altitude and water temperature at local spatial scales. Nonetheless, further investigations would be needed to clearly differentiate between the effects of anthropogenic and natural causes on biological monitoring at larger spatial scales.     

A modular approach to Integrated Assessment modeling

In this paper, we present a new approach to model coupling that probably forms the methodological basis of a new generation of Integrated Assessment models. This approach respects the knowledge and expertise that is embodied in existing models and encourages their gradual evolution. Modularity is the guiding principle. Our approach is distinguished by the way modules are coupled which is based on an interplay of a job control module, a numerical coupling module, and a couple of stand-alone functional modules. The numerical coupling module - the core component - serves to treat the feedbacks between the functional modules. A first implemented example that couples an economic and a climate module by means of a two-phase meta-optimization is presented here. The algorithm and mathematical structure behind are discussed as well as important features such as convergence behavior and reliability.     

Optimizing the removal of small fish passage barriers

Removing small artificial barriers that hinder upstream migrations of fish is a major problem in riparian habitat restoration. Because of budgetary limitations, it is necessary to prioritize barrier removal and repair decisions. These have usually been based on scoring and ranking procedures, which, although simple to use, can be very inefficient in terms of increasing the amount of accessible instream habitat. We develop a novel decision-making approach, based on integer programming techniques, which optimizes repair and removal decisions. Results show based on real datasets of barrier culverts located in Washington State that scoring and ranking is over 25% below the optimum on average and a full 100% below in the worst case, producing no net habitat gain whatsoever. This is compared to a dynamic programming method that was able to find optimal solutions in less than a second, even for problems with up to several hundred variables, and a heuristic method, which found solutions with less than a 1% average optimality gap in even less time.     

The modern theory of biological evolution: an expanded synthesis

In 1858, two naturalists, Charles Darwin and Alfred Russel Wallace, independently proposed natural selection as the basic mechanism responsible for the origin of new phenotypic variants and, ultimately, new species. A large body of evidence for this hypothesis was published in Darwins Origin of Species one year later, the appearance of which provoked other leading scientists like August Weismann to adopt and amplify Darwins perspective. Weismanns neo-Darwinian theory of evolution was further elaborated, most notably in a series of books by Theodosius Dobzhansky, Ernst Mayr, Julian Huxley and others. In this article we first summarize the history of life on Earth and provide recent evidence demonstrating that Darwins dilemma (the apparent missing Precambrian record of life) has been resolved. Next, the historical development and structure of the modern synthesis is described within the context of the following topics: paleobiology and rates of evolution, mass extinctions and species selection, macroevolution and punctuated equilibrium, sexual reproduction and recombination, sexual selection and altruism, endosymbiosis and eukaryotic cell evolution, evolutionary developmental biology, phenotypic plasticity, epigenetic inheritance and molecular evolution, experimental bacterial evolution, and computer simulations (in silico evolution of digital organisms). In addition, we discuss the expansion of the modern synthesis, embracing all branches of scientific disciplines. It is concluded that the basic tenets of the synthetic theory have survived, but in modified form. These sub-theories require continued elaboration, particularly in light of molecular biology, to answer open-ended questions concerning the mechanisms of evolution in all five kingdoms of life.Dedicated to Prof. Dr. Dr. hc mult. Ernst Mayr on the occasion of his 100th birthdayThis revised version was published online in March 2004, with corrections to the caption of Figure 6.